More than 87,000 scientific articles on COVID-19 were published between the start of the pandemic and October of 2020 (https://news.osu.edu/more-than-87000-scientific-papers-on-coronavirus-since-pandemic/). More than 720,000 unique authors have contributed to COVID-19 articles as of August, 2021 (https://royalsocietypublishing.org/doi/10.1098/rsos.210389 ). Having an article which was published in the Optimal Data Analysis journal cited by the World Health Organization (WHO), … Continue reading Tremendous Honor: World Health Organization Cites ODA article on influence of mask mandates on COVID-19 infections
Overview of the Optimal Discriminant Analysis and Novometric Paradigm
Paul R. Yarnold, Ph.D., Nathaniel J. Rhodes, Pharm.D., Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC; Chicago College of Pharmacy, Midwestern University; Linden Consulting Group, LLC Overviews of optimal discriminant analysis (ODA) and novometric theory are presented. Discussion addresses the role of accuracy in translational and precision forecasting research, and of parsimony in theoretical research; the … Continue reading Overview of the Optimal Discriminant Analysis and Novometric Paradigm
MegaODA software within R: Package now available on GitHub
To run the MegaODA software within R, download the ODA package for R available at GitHub and created by Dr. Nathaniel J. Rhodes and Dr. Paul Yarnold. This package serves as an interface for the MegaODA software suite. To utilize this package obtain a licensed copy of the MegaODA software. Once MegaODA is obtained and … Continue reading MegaODA software within R: Package now available on GitHub
Running MegaODA and CTA Software within Stata
Dr. Ariel Linden created and published the Stata programs for running MegaODA and CTA software. To run MegaODA and CTA software within Stata refer to ODA articles discussing this topic in the article’s title.
Evaluating Treatment Effects in Longitudinal Panel Data Using ODA from Within Stata
Ariel Linden, Dr.P.H., Paul R. Yarnold, Ph.D. Linden Consulting Group, LLC, Optimal Data Analysis, LLC This paper demonstrates how ODA can be used to estimate treatment effects in longitudinal panel data using the oda Stata package. View journal article
Why do Research, and How to Publish Your First Paper
Zoom Presentation (April 24, 2021), Hackoverflow Technical Society, Chandigarh University, India https://youtu.be/4bMLjx-uMdw
Using ODA to Estimate Propensity-Weight-Adjusted Treatment Effects for Multi-Valued Treatments
Paul R. Yarnold, Ph.D., Fred B. Bryant, Ph.D., Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC, Loyola University Chicago, Linden Consulting Group, LLC We demonstrate the use of optimal data analysis to obtain a hierarchically optimal classification tree-based propensity score model for an application with three (treatment) groups, and to assess outcome differences between treatment groups … Continue reading Using ODA to Estimate Propensity-Weight-Adjusted Treatment Effects for Multi-Valued Treatments
Implementing ODA from Within Stata: Evaluating Test-Retest Reliability of Positive and Negative Emotional States, vs. Personality Traits, Assessed Using Likert Scales, for Males vs. Females
Paul R. Yarnold, Ph.D. and Ariel Linden, Dr.P.H. Optimal Data Analysis, LLC and Linden Consulting Group, LLC This paper illustrates testing directional hypotheses for test-retest Likert ratings of positive and negative emotional states and personality traits for males and females, using the Stata package for implementing ODA. View journal article
Executing ODA from Within Stata: Combining Random Forests and ODA to Estimate Treatment Effects for Multi-Valued Treatments (Invited)
Ariel Linden, Dr. P.H. Linden Consulting Group, LLC This paper demonstrates how the random forest algorithm can be used in conjunction with ODA to estimate treatment effects for multivalued treatments using the new Stata package for implementing ODA. View journal article
Implementing ODA from Within Stata: Assessing Split-Half Reliability Using a Polychotomous Attribute
Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing a directional (i.e., confirmatory) hypotheses for a split-half reliability study using a polychotomous attribute having four categories, via the Stata package for implementing ODA. View journal article
Implementing ODA from Within Stata: Assessing Parallel-Forms Reliability Using a Binary and an Ordered Attribute
Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing a directional (i.e., confirmatory) hypotheses for a parallel-forms reliability study using a binary and an ordered measure, via the Stata package for implementing ODA. View journal article
Executing ODA from Within Stata: Combining Boosted Regression and ODA to Estimate Treatment Effects for Multi-Valued Treatments
Ariel Linden, Dr. P.H. and Paul R. Yarnold, Ph.D. Linden Consulting Group, LLC & Optimal Data Analysis, LLC This paper demonstrates how boosted regression can be used in conjunction with ODA to estimate treatment effects for multivalued treatments using the new Stata package for implementing ODA. View journal article
Implementing ODA from Within Stata: Confirmatory and Exploratory Inter-Rater Reliability Hypothesis with a Three-Category Ordinal Rating
Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper illustrates testing directional (confirmatory) and non-directional (exploratory) hypotheses for an inter-rater reliability study using a three-category ordinal measure, via the Stata package for implementing ODA. View journal article
Implementing ODA from Within Stata: Exploratory Hypothesis, Three-Category Class Variable, Continuous Attribute
Paul R. Yarnold, Ph.D. and Ariel Linden, Dr. P.H. Optimal Data Analysis, LLC & Linden Consulting Group, LLC This paper describes how to test a non-directional (exploratory) hypothesis for a design relating a three-category class (“dependent”) variable and a continuous attribute vis-à-vis the Stata package for implementing ODA. View journal article
Mask Mandates Can Rapidly and Efficiently Limit COVID-19 Spread: Month-Over-Month Effectiveness of Governmental Policies in Reducing the Number of New COVID-19 Cases in 37 US States and the District of Columbia
Michael J. Maloney, Nathaniel J. Rhodes & Paul R. Yarnold Proof School, Midwestern University & Optimal Data Analysis LLC SARS-CoV-2 is the beta-coronavirus responsible for COVID-19. Facemask use has been qualitatively associated with reduced COVID-19 cases, but no study has quantitatively assessed the impact of government mask mandates (MM) on new COVID-19 cases across multiple … Continue reading Mask Mandates Can Rapidly and Efficiently Limit COVID-19 Spread: Month-Over-Month Effectiveness of Governmental Policies in Reducing the Number of New COVID-19 Cases in 37 US States and the District of Columbia
Mask Mandate Prevented COVID-19 Deaths in Minnesota
Michael J. Maloney Proof School As the number of COVID-19 deaths in the US increased, various policies were enacted in an effort to slow the spread of the pandemic. As sufficient data accumulate over time, the impact of policy on public health outcomes may be statistically evaluated. The present paper uses ODA to evaluate the … Continue reading Mask Mandate Prevented COVID-19 Deaths in Minnesota
Novometric Temporal Analysis of Monthly Otolaryngology Service Consults Over Five Consecutive Years
Paul R. Yarnold, Ph.D. Optimal Data Analysis, LLC Statistically unmotivated exploratory parametric analysis reported that the mean number of monthly consults at an academic otolaryngology service in 2014-2015 was significantly lower than in 2017-2018, suggesting a trend involving increasing numbers of consults over time. Evaluating these data, exploratory novometric temporal analysis identified a globally optimal … Continue reading Novometric Temporal Analysis of Monthly Otolaryngology Service Consults Over Five Consecutive Years
Simplified Method for Running MegaODA and CTA Software on Modern Windows Systems Using “Drag and Drop” Functionality
Michael J. Maloney Proof School Users running MegaODA and/or CTA software using the Windows-10 operating system may execute programs more efficiently than vis-à-vis the standard procedure of using the command prompt. View journal article
Comparing CTA to Boosted Regression for Estimating the Propensity Score (Invited)
Ariel Linden Linden Consulting Group, LLC Boosted regression (BR) has been recommended as a machine learning alternative to logistic regression for estimating the propensity score because of its greater accuracy. Commonly known as multiple additive regression trees, BR is a general, automated, data-adaptive modelling algorithm which can estimate the non-linear relationship between treatment assignment (the … Continue reading Comparing CTA to Boosted Regression for Estimating the Propensity Score (Invited)
Differing Cancer-Incidence Rates of Male vs. Female Americans
Paul R. Yarnold Optimal Data Analysis LLC Novometric classification tree analysis was used to evaluate Surveillance, Epidemiology, and End Results (SEER) Program data to discover cancer sites moderately or relatively strongly predicted by male vs. female gender. Future research using any of the 13 cancer sites which met this criterion should account for gender using … Continue reading Differing Cancer-Incidence Rates of Male vs. Female Americans
Disparate Cancer-Incidence Rates of Caucasian vs. African Americans
Paul R. Yarnold Optimal Data Analysis LLC Surveillance, Epidemiology and End Results (SEER) Program data were used to find cancer sites with at least moderately different rates for African vs. Caucasian Americans. Future research in ten cancer sites which involves subjects represented by these groups should account for associated cancer-incidence disparity in matching or via … Continue reading Disparate Cancer-Incidence Rates of Caucasian vs. African Americans
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